entropy_fl()

Applies to: ✅ Microsoft Fabric ✅ Azure Data Explorer ✅ Azure Monitor ✅ Microsoft Sentinel

The function entropy_fl() is a user-defined function (UDF) that calculates the Shannon Entropy of multiple probability vectors.

Syntax

T | invoke entropy_fl(val_col)

Learn more about syntax conventions.

Parameters

Name	Type	Required	Description
val_col	string	✔️	The name of the column containing the probability vectors.

Function definition

You can define the function by either embedding its code as a query-defined function, or creating it as a stored function in your database, as follows:

Query-defined

Define the function using the following let statement. No permissions are required.

Important

A let statement can't run on its own. It must be followed by a tabular expression statement. To run a working example of time_weighted_avg_fl(), see Example.

let entropy_fl=(tbl:(*), val_col:string)
{
	tbl
    | extend _vals = column_ifexists(val_col, dynamic(null))
    | mv-apply pa=_vals to typeof(real) on 
    (summarize H=sum(-pa*log2(pa)))
    | project-away _vals
};
// Write your query to use the function here.

Stored

Define the stored function once using the following .create function. Database User permissions are required.

Important

You must run this code to create the function before you can use the function as shown in the Example.

.create-or-alter function with (folder = "Packages\\Stats", docstring = "Shannon entropy")
entropy_fl(tbl:(*), val_col:string)
{
	tbl
    | extend _vals = column_ifexists(val_col, dynamic(null))
    | mv-apply pa=_vals to typeof(real) on 
    (summarize H=sum(-pa*log2(pa)))
    | project-away _vals
}

Example

The following example uses the invoke operator to run the function.

Query-defined

To use a query-defined function, invoke it after the embedded function definition.

let entropy_fl=(tbl:(*), val_col:string)
{
	tbl
    | extend _vals = column_ifexists(val_col, dynamic(null))
    | mv-apply pa=_vals to typeof(real) on 
    (summarize H=sum(-pa*log2(pa)))
    | project-away _vals
};
let probs = datatable(p:dynamic) [
    dynamic([0.2, 0.4, 0.3, 0.1]),
    dynamic([0.5, 0.5])
];
probs
| invoke entropy_fl('p')

Stored

Important

For this example to run successfully, you must first run the Function definition code to store the function.

let probs = datatable(p:dynamic) [
    dynamic([0.2, 0.4, 0.3, 0.1]),
    dynamic([0.5, 0.5])
];
probs
| invoke entropy_fl('p')

Output

p	H
[0.2, 0.4, 0.3, 0.1]	1.84643934467102
[0.5, 0.5]	1